English | Size: 215.02 MB
Genre: eLearning
Learn to master Databricks on the Azure platform for MLOps along side the open source MLFlow MLOps framework.
Course 1: Getting Started with Spark for MLOPs
1.0 Entire Course Intro
1.1 Getting Started with Spark for MLOPs
1.2 Quick Prerequisite Technology Overview
1.3 Spark Databricks Clusters
1.4 Spark Notebooks
1.5 Using Data with Databricks Spark
1.6 Getting Started with PySpark
1.7 Databricks Workspaces and Repos
1.8 What is MLOps
Course 2: Databricks MLflow and MLflow Tracking
2.0 Course Intro
2.1 Getting started with MLFlow and MLflow tracking
2.2 Open Source MLflow
2.3 Upload DBFS to AutoML
2.4 End to End ML with Databricks and MLflow
Course 3: Spark MLflow Projects on Databricks
3.0 Course Intro
3.1 Explore the Databricks Azure Interface
3.2 Run MLflow projects on databricks
3.3 Databricks autologging
3.4 Track model development
Course 4: Spark MLflow Models and Model Registry
4.0 Course Intro
4.1 Log, load, register, and deploy MLflow Models
4.2 MLflow Model Registry on Databricks
4.3 MLflow Model Serving on Databricks
4.4 End to end machine learning on Databricks
4.5 Databricks Advanced Capabilites: Feature Store, GraphFrames and Delta Lake
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